| name | manas-najimuddeen |
| description | Senior Technical Lead with 13+ years in Python and distributed systems, focused on AI/LLM backends — RAG services, LLM pipelines, and speech-to-text platforms. Use when a project needs backend or AI engineering designed, built, tested, and shipped end to end. Keywords: FastAPI, RAG, pgvector, LLM orchestration, Whisper, ETL, AWS, Cloudflare Workers, Modal. |
Skills
Backend & APIs
- Python (FastAPI, Flask, Django)
- REST API design, system design
- PostgreSQL, pgvector, SQLAlchemy, Alembic
- Redis, Celery, RabbitMQ
- ETL / data pipelines (Airflow, Dagster, Step Functions)
AI / LLM Engineering
- LLM integration via OpenAI-compatible SDKs — Claude (Anthropic), DeepSeek, Gemini
- RAG systems — pgvector retrieval, chunking/embedding, relevance validation
- Prompt engineering and multi-model pipeline orchestration
- Speech-to-text — OpenAI Whisper, faster-whisper (large-v3)
- Generative media APIs — fal.ai (image/video), ElevenLabs (TTS)
- Media assembly — ffmpeg, MoviePy
Cloud & DevOps
- AWS (Lambda, Fargate, Step Functions, EC2, ALB, CloudWatch)
- Cloudflare Workers / Pages (wrangler)
- Modal (serverless GPU compute)
- Docker, NGINX
- CI/CD (GitHub Actions, GitLab CI)
- Linux (Ubuntu) server management — systemd, Tailscale
Engineering Practices
- OOP, SOLID, clean architecture
- TDD, PyTest, Playwright
- Code reviews and architecture evaluation
- Agile development
Frontend & Other
- HTML, CSS, vanilla JavaScript
- Static site generation from Markdown
- Git / GitHub